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miRSM: an R package to infer and analyse miRNA sponge modules in heterogeneous data

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dc.contributor.authorZhang, J.
dc.contributor.authorLiu, L.
dc.contributor.authorXu, T.
dc.contributor.authorZhang, W.
dc.contributor.authorZhao, C.
dc.contributor.authorLi, S.
dc.contributor.authorLi, J.
dc.contributor.authorRao, N.
dc.contributor.authorLe, T.D.
dc.date.issued2021
dc.descriptionData source: , https://doi.org/10.1080/15476286.2021.1905341
dc.description.abstractIn molecular biology, microRNA (miRNA) sponges are RNA transcripts which compete with other RNA transcripts for binding with miRNAs. Research has shown that miRNA sponges have a fundamental impact on tissue development and disease progression. Generally, to achieve a specific biological function, miRNA sponges tend to form modules or communities in a biological system. Until now, however, there is still a lack of tools to aid researchers to infer and analyse miRNA sponge modules from heterogeneous data. To fill this gap, we develop an R/Bioconductor package, <i>miRSM</i>, for facilitating the procedure of inferring and analysing miRNA sponge modules. <i>miRSM</i> provides a collection of 50 co-expression analysis methods to identify gene co-expression modules (which are candidate miRNA sponge modules), four module discovery methods to infer miRNA sponge modules and seven modular analysis methods for investigating miRNA sponge modules. <i>miRSM</i> will enable researchers to quickly apply new datasets to infer and analyse miRNA sponge modules, and will consequently accelerate the research on miRNA sponges.
dc.identifier.citationRNA Biology, 2021; 18(12):2308-2320
dc.identifier.doi10.1080/15476286.2021.1905341
dc.identifier.issn1547-6286
dc.identifier.issn1555-8584
dc.identifier.orcidLe, T.D. [0000-0002-9732-4313]
dc.identifier.urihttps://hdl.handle.net/11541.2/147337
dc.language.isoen
dc.publisherTAYLOR & FRANCIS INC
dc.relation.granthttp://purl.org/au-research/grants/arc/202001AT070024
dc.rightsCopyright 2021 Informa UK Limited, trading as Taylor & Francis Group Access Condition Notes: Accepted manuscript available after 1 July 2022
dc.source.urihttps://doi.org/10.1080/15476286.2021.1905341
dc.subjectHumans
dc.subjectMicroRNAs
dc.subjectRNA, Messenger
dc.subjectGene Expression Regulation
dc.subjectBinding, Competitive
dc.subjectSoftware
dc.subjectGene Regulatory Networks
dc.titlemiRSM: an R package to infer and analyse miRNA sponge modules in heterogeneous data
dc.typeJournal article
pubs.publication-statusPublished
ror.fileinfo12238636800001831 13238636790001831 CS miRSM
ror.mmsid9916506101201831

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